Nanopore sequencing: a rapid solution for infectious disease epidemics

Comparative Evaluation of Open-Source Bioinformatics Pipelines for Full-Length Viral Genome Assembly

The increasingly widespread application of next-generation sequencing (NGS) in clinical diagnostics and epidemiological research has generated a demand for robust, fast, automated, and user-friendly bioinformatics workflows. To guide the choice of tools for the assembly of full-length viral genomes from NGS datasets, we assessed the performance and applicability of four open-source bioinformatics pipelines (shiver-for which we created a user-friendly Dockerized version, referred to as dshiver; SmaltAlign; viral-ngs; and V-pipe) using both simulated and real-world HIV-1 paired-end short-read datasets and default settings. All four pipelines produced consensus genome assemblies with high quality metrics (genome fraction recovery, mismatch and indel rates, variant calling F1 scores) when the reference sequence used for assembly had high similarity to the analyzed sample. The shiver and SmaltAlign pipelines (but not viral-ngs and V-Pipe) also showed robust performance with more divergent samples (non-matching subtypes). With empirical datasets, SmaltAlign and viral-ngs exhibited an order of magnitude shorter runtime compared to V-Pipe and shiver. In terms of applicability, V-Pipe provides the broadest functionalities, SmaltAlign and dshiver combine user-friendliness with robustness, while the use of viral-ngs requires less computational resources compared to other pipelines. In conclusion, if a closely matched reference sequence is available, all pipelines can reliably reconstruct viral consensus genomes; therefore, differences in user-friendliness and runtime may guide the choice of the pipeline in a particular setting. If a matched reference sequence cannot be selected, we recommend shiver or SmaltAlign for robust performance. The new Dockerized version of shiver offers ease of use in addition to the accuracy and robustness of the original pipeline.

Laboratory tools for the direct detection of bacterial respiratory infections and antimicrobial resistance: a scoping review

Rapid laboratory tests are urgently required to inform antimicrobial use in food animals. Our objective was to synthesize knowledge on the direct application of long-read metagenomic sequencing to respiratory samples to detect bacterial pathogens and antimicrobial resistance genes (ARGs) compared to PCR, loop-mediated isothermal amplification, and recombinase polymerase amplification. Our scoping review protocol followed the Joanna Briggs Institute and PRISMA Scoping Review reporting guidelines. Included studies reported on the direct application of these methods to respiratory samples from animals or humans to detect bacterial pathogens ±ARGs and included turnaround time (TAT) and analytical sensitivity. We excluded studies not reporting these or that were focused exclusively on bioinformatics. We identified 5,636 unique articles from 5 databases. Two-reviewer screening excluded 3,964, 788, and 784 articles at 3 levels, leaving 100 articles (19 animal and 81 human), of which only 7 studied long-read sequencing (only 1 in animals). Thirty-two studies investigated ARGs (only one in animals). Reported TATs ranged from minutes to 2 d; steps did not always include sample collection to results, and analytical sensitivity varied by study. Our review reveals a knowledge gap in research for the direct detection of bacterial respiratory pathogens and ARGs in animals using long-read metagenomic sequencing. There is an opportunity to harness the rapid development in this space to detect multiple pathogens and ARGs on a single sequencing run. Long-read metagenomic sequencing tools show potential to address the urgent need for research into rapid tests to support antimicrobial stewardship in food animal production.

Comparison of nine extraction methods for bacterial identification using the ONT MinION sequencer

The Anthrax mailings bioterrorism attack in 2001 revealed the need for universal and rapid microbial forensic analyses on unknown biological evidence. However, the gold standard for bacterial identification includes culturing isolates, which is laborious. Molecular approaches for bacterial identification revolve around 16S ribosomal gene sequencing using Sanger or next generation sequencing (NGS) platforms, but these techniques are laboratory-based and can also be time-consuming. The Oxford Nanopore Technologies (ONT) MinION sequencer can generate long read lengths that span the entire bacterial 16S rRNA gene and accurately identify the species level. This platform can be used in the field, allowing on-site evidence analysis. However, it requires higher quantities of pure DNA compared to other sequencing platforms; thus, the extraction method for bacterial DNA is critical for downstream analysis, which to date are tailored toward a priori knowledge of the species' taxonomic grouping. During an attack, the investigative team may not know what species they are handling; therefore, identifying an extraction method that can handle all bacterial groups and generate clean DNA for the MinION is useful for microbial forensic analysis. The purpose of this study was to identify a "universal" extraction method that can be coupled with ONT MinION sequencing for use in forensic situations for rapid identification. It also evaluated the cloud-based data analysis software provided by ONT, EPI2ME. No "universal" extraction method was identified as optimal for downstream MinION sequencing. However, the DNeasy PowerSoil Kit and Noda et al. Chelex-100 method gave comparable sequencing results and could be used as rapid extraction techniques. This study showed that the ONT 16S Barcoding Kit 1-24 coupled with the 16S FASTQ workflow might not be the best for use in forensic situations where species-level identification needs to be obtained, as most alignments were approximately 89% accurate. In all seven test organisms and nine extraction methods, accurate species identification was only obtained in 63% of the cases.

Nanopore targeted sequencing-based diagnosis of central nervous system infections in HIV-infected patients

BACKGROUND

Early and accurate etiological diagnosis is very important for improving the prognosis of central nervous system (CNS) infections in human immunodeficiency virus (HIV)-infected patients. The goal is not easily achieved by conventional microbiological tests. We developed a nanopore targeted sequencing (NTS) platform and evaluated the diagnostic performance for CNS infections in HIV-infected patients, with special focus on cryptococcal meningitis (CM). We compared the CM diagnostic performance of NTS with conventional methods and cryptococcal polymerase chain reaction (PCR).

METHODS

This study included 57 hospitalized HIV-infected patients with suspected CNS infections from September 2018 to March 2022. The diagnosis established during hospitalization includes 27 cases of CM, 13 CNS tuberculosis, 5 toxoplasma encephalitis, 2 cytomegalovirus (CMV) encephalitis and 1 Varicella-zoster virus (VZV) encephalitis. The 2 cases of CMV encephalitis also have co-existing CM. Target-specific PCR amplification was used to enrich pathogen sequences before nanopore sequencing. NTS was performed on stored cerebrospinal fluid (CSF) samples and the results were compared with the diagnosis during hospitalization.

RESULTS

53 (93.0%) of the patients were male. The median CD4 cell count was 25.0 (IQR: 14.0-63.0) cells/uL. The sensitivities of CSF culture, India ink staining, cryptococcal PCR and NTS for CM were 70.4% (95%CI: 51.5 - 84.1%), 76.0% (95%CI: 56.6 - 88.5%), 77.8% (59.2 - 89.4%) and 85.2% (95%CI: 67.5 - 94.1%), respectively. All those methods had 100% specificity for CM. Our NTS platform could identify Cryptococcus at species level. Moreover, NTS was also able to identify all the 5 cases of toxoplasma encephalitis, 2 cases of CMV encephalitis and 1 VZV encephalitis. However, only 1 of 13 CNS tuberculosis cases was diagnosed by NTS, and so did Xpert MTB/RIF assay.

CONCLUSIONS

NTS has a good diagnostic performance for CM in HIV-infected patients and may have the ability of simultaneously detecting other pathogens, including mixed infections. With continuing improving of the NTS platform, it may be a promising alterative microbiological test for assisting with the diagnosis of CNS infections.

Identification of Viruses Infecting Phalaenopsis Orchids Using Nanopore Sequencing and Development of an RT-RPA-CRISPR/Cas12a for Rapid Visual Detection of Nerine Latent Virus

Phalaenopsis orchids are one of the most popular ornamental plants. More than thirty orchid viruses have been reported, and virus-infected Phalaenopsis orchids significantly lose their commercial value. Therefore, the development of improved viral disease detection methods could be useful for quality control in orchid cultivation. In this study, we first utilized the MinION, a portable sequencing device based on Oxford Nanopore Technologies (ONT) to rapidly detect plant viruses in Phalaenopsis orchids. Nanopore sequencing revealed the presence of three plant viruses in Phalaenopsis orchids: odontoglossum ringspot virus, cymbidium mosaic virus, and nerine latent virus (NeLV). Furthermore, for the first time, we detected NeLV infection in Phalaenopsis orchids using nanopore sequencing and developed the reverse transcription-recombinase polymerase amplification (RT-RPA)-CRISPR/Cas12a method for rapid, instrument-flexible, and accurate diagnosis. The developed RT-RPA-CRISPR/Cas12a technique can confirm NeLV infection in less than 20 min and exhibits no cross-reactivity with other viruses. To determine the sensitivity of RT-RPA-CRISPR/Cas12a for NeLV, we compared it with RT-PCR using serially diluted transcripts and found a detection limit of 10 zg/μL, which is approximately 1000-fold more sensitive. Taken together, the ONT platform offers an efficient strategy for monitoring plant viral pathogens, and the RT-RPA-CRISPR/Cas12a method has great potential as a useful tool for the rapid and sensitive diagnosis of NeLV.

Nanopore Metagenomics Sequencing for Rapid Diagnosis and Characterization of Lily Viruses

Lilies (Lilium spp.) are one of the most important ornamental flower crops grown in Korea. Most viral diseases in lilies are transmitted by infected bulbs, which cause serious economic losses due to reduced yields. Various diagnostic techniques and high-throughput sequencing methods have been used to detect lily viruses. According to Oxford Nanopore Technologies (ONT), MinION is a compact and portable sequencing device. In this study, three plant viruses, lily mottle, lily symptomless, and plantago asiatica mosaic virus, were detected in lily samples using the ONT platform. As a result of genome assembly of reads obtained through ONT, 100% coverage and 90.3-93.4% identity were obtained. Thus, we show that the ONT platform is a promising tool for the diagnosis and characterization of viruses that infect crops.

Diagnosis of pathogens causing bacterial meningitis using Nanopore sequencing in a resource-limited setting

Aim

The aim of the present study is to compare the performance of 16S rRNA Nanopore sequencing and conventional culture in detecting infectious pathogens in patients with suspected meningitis in a resource-limited setting without extensive bioinformatics expertise.

Methods

DNA was isolated from the cerebrospinal fluid (CSF) of 30 patients with suspected bacterial meningitis. The isolated DNA was subjected to 16S sequencing using MinION™. The data were analysed in real time via the EPI2ME cloud platform. The Nanopore sequencing was done in parallel to routine microbiological diagnostics.

Results

Nanopore sequencing detected bacterial pathogens to species level in 13 of 30 (43%) samples. CSF culture showed 40% (12/30) positivity. In 21 of 30 patients (70%) with suspected bacterial meningitis, both methods yielded concordant results. About nine of 30 samples showed discordant results, of these five were false positive and four were false negative. In five of the culture negative results, nanopore sequencing was able to detect pathogen genome, due to the higher sensitivity of the molecular diagnostics. In two other samples, the CSF culture revealed Cryptococcus neoformans and Streptococcus pneumoniae, which were not detected by Nanopore sequencing. Overall, using both the cultures and 16S Nanopore sequencing, positivity rate increased from 40% (12/30) to 57% (17/30).

Conclusion

Next-generation sequencing could detect pathogens within six hours and could become an important tool for both pathogen screening and surveillance in low- and middle-income countries (LMICs) that do not have direct access to extensive bioinformatics expertise.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12941-022-00530-6.

Grapevine Virology in the Third-Generation Sequencing Era: From Virus Detection to Viral Epitranscriptomics

Among all economically important plant species in the world, grapevine (Vitis vinifera L.) is the most cultivated fruit plant. It has a significant impact on the economies of many countries through wine and fresh and dried fruit production. In recent years, the grape and wine industry has been facing outbreaks of known and emerging viral diseases across the world. Although high-throughput sequencing (HTS) has been used extensively in grapevine virology, the application and potential of third-generation sequencing have not been explored in understanding grapevine viruses and their impact on the grapevine. Nanopore sequencing, a third-generation technology, can be used for the direct sequencing of both RNA and DNA with minimal infrastructure. Compared to other HTS methods, the MinION nanopore platform is faster and more cost-effective and allows for long-read sequencing. Due to the size of the MinION device, it can be easily carried for field viral disease surveillance. This review article discusses grapevine viruses, the principle of third-generation sequencing platforms, and the application of nanopore sequencing technology in grapevine virus detection, virus-plant interactions, as well as the characterization of viral RNA modifications.

Current Developments and Challenges in Plant Viral Diagnostics: A Systematic Review

Plant viral diseases are the foremost threat to sustainable agriculture, leading to several billion dollars in losses every year. Many viruses infecting several crops have been described in the literature; however, new infectious viruses are emerging frequently through outbreaks. For the effective treatment and prevention of viral diseases, there is great demand for new techniques that can provide accurate identification on the causative agents. With the advancements in biochemical and molecular biology techniques, several diagnostic methods with improved sensitivity and specificity for the detection of prevalent and/or unknown plant viruses are being continuously developed. Currently, serological and nucleic acid methods are the most widely used for plant viral diagnosis. Nucleic acid-based techniques that amplify target DNA/RNA have been evolved with many variants. However, there is growing interest in developing techniques that can be based in real-time and thus facilitate in-field diagnosis. Next-generation sequencing (NGS)-based innovative methods have shown great potential to detect multiple viruses simultaneously; however, such techniques are in the preliminary stages in plant viral disease diagnostics. This review discusses the recent progress in the use of NGS-based techniques for the detection, diagnosis, and identification of plant viral diseases. New portable devices and technologies that could provide real-time analyses in a relatively short period of time are prime important for in-field diagnostics. Current development and application of such tools and techniques along with their potential limitations in plant virology are likewise discussed in detail.

Sequencing barcode construction and identification methods based on block error-correction codes

Multiplexed sequencing relies on specific sample labels, the barcodes, to tag DNA fragments belonging to different samples and to separate the output of the sequencers. However, the barcodes are often corrupted by insertion, deletion and substitution errors introduced during sequencing, which may lead to sample misassignment. In this paper, we propose a barcode construction method, which combines a block error-correction code with a predetermined pseudorandom sequence to generate a base sequence for labeling different samples. Furthermore, to identify the corrupted barcodes for assigning reads to their respective samples, we present a soft decision identification method that consists of inner decoding and outer decoding. The inner decoder establishes the hidden Markov model (HMM) for base insertion/deletion estimation with the pseudorandom sequence, and adapts the forward-backward (FB) algorithm to output the soft information of each bit in the block code. The outer decoder performs soft decision decoding using the soft information to effectively correct multiple errors in the barcodes. Simulation results show that the proposed methods are highly robust to high error rates of insertions, deletions and substitutions in the barcodes. In addition, compared with the inner decoding algorithm of the barcodes based on watermarks, the proposed inner decoding algorithm can greatly reduce the decoding complexity.